Nonparametric estimation of returns to scale using input distance functions: an application to large US banks

We derive new measures of returns to scale based on input distance functions (IDFs) and estimate them using nonparametric regression methods. In contrast to the cost function approach, the IDF does not require input prices which are usually unavailable or measured imprecisely. In addition, we can ac...

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Autores:
Restrepo-Tobón, Diego
Kumbhakar, Subal C.
Tipo de recurso:
Fecha de publicación:
2015
Institución:
Universidad EAFIT
Repositorio:
Repositorio EAFIT
Idioma:
eng
OAI Identifier:
oai:repository.eafit.edu.co:10784/7613
Acceso en línea:
http://hdl.handle.net/10784/7613
Palabra clave:
Nonparametric regression
Returns to scale
Distance functions
Banks
Rights
License
restrictedAccess
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oai_identifier_str oai:repository.eafit.edu.co:10784/7613
network_acronym_str REPOEAFIT2
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repository_id_str
spelling 20152015-11-06T21:15:34Z20152015-11-06T21:15:34Z0377-7332http://hdl.handle.net/10784/761310.1007/s00181-014-0831-9We derive new measures of returns to scale based on input distance functions (IDFs) and estimate them using nonparametric regression methods. In contrast to the cost function approach, the IDF does not require input prices which are usually unavailable or measured imprecisely. In addition, we can account for equity and physical capital in the IDF. These variables are either excluded from the analysis (especially in a cost function approach) or treated as quasi-fixed inputs, because their prices are not readily available. In our application, we use data for bank holding companies and large commercial banks in the U.S. from 2000 to 2010. We find that although some of these institutions enjoy increasing returns to scale, scale economies are economically small. Thus, concerns about potential cost increases arising from breaking up large banking organizations seem exaggerated, especially from the scale economies point of view.engSpringer International Publishing Empirical Economics. Vol. 48, (1), 2015, pp.143-168http://link.springer.com/article/10.1007/s00181-014-0831-9http://link.springer.com/article/10.1007/s00181-014-0831-9restrictedAccess© Springer International Publishing AG, Part of Springer Science+Business MediaAcceso restringidohttp://purl.org/coar/access_right/c_16ecEmpirical Economics. Vol. 48, (1), 2015, pp.143-168Nonparametric estimation of returns to scale using input distance functions: an application to large US banksarticleinfo:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersionArtículoObra publicadapublishedVersionhttp://purl.org/coar/version/c_970fb48d4fbd8a85http://purl.org/coar/resource_type/c_6501http://purl.org/coar/resource_type/c_2df8fbb1Nonparametric regressionReturns to scaleDistance functionsBanksEconomía y FinanzasFinanzasRestrepo-Tobón, DiegoKumbhakar, Subal C.EAFIT UniversityBinghamton UniversityGrupo de Investigación Finanzas y BancaEmpirical Economics481143168ORIGINALs00181-014-0831-9.pdfs00181-014-0831-9.pdfapplication/pdf373513https://repository.eafit.edu.co/bitstreams/4781c051-09d1-48b4-a564-c051efcb5861/download9834acc3ca934972ed37ac4e76bf24cbMD5110784/7613oai:repository.eafit.edu.co:10784/76132023-03-15 08:19:10.923open.accesshttps://repository.eafit.edu.coRepositorio Institucional Universidad EAFITrepositorio@eafit.edu.co
dc.title.eng.fl_str_mv Nonparametric estimation of returns to scale using input distance functions: an application to large US banks
title Nonparametric estimation of returns to scale using input distance functions: an application to large US banks
spellingShingle Nonparametric estimation of returns to scale using input distance functions: an application to large US banks
Nonparametric regression
Returns to scale
Distance functions
Banks
title_short Nonparametric estimation of returns to scale using input distance functions: an application to large US banks
title_full Nonparametric estimation of returns to scale using input distance functions: an application to large US banks
title_fullStr Nonparametric estimation of returns to scale using input distance functions: an application to large US banks
title_full_unstemmed Nonparametric estimation of returns to scale using input distance functions: an application to large US banks
title_sort Nonparametric estimation of returns to scale using input distance functions: an application to large US banks
dc.creator.fl_str_mv Restrepo-Tobón, Diego
Kumbhakar, Subal C.
dc.contributor.department.spa.fl_str_mv Economía y Finanzas
Finanzas
dc.contributor.author.spa.fl_str_mv Restrepo-Tobón, Diego
Kumbhakar, Subal C.
dc.contributor.affiliation.spa.fl_str_mv EAFIT University
Binghamton University
dc.contributor.program.spa.fl_str_mv Grupo de Investigación Finanzas y Banca
dc.subject.keyword.eng.fl_str_mv Nonparametric regression
Returns to scale
Distance functions
Banks
topic Nonparametric regression
Returns to scale
Distance functions
Banks
description We derive new measures of returns to scale based on input distance functions (IDFs) and estimate them using nonparametric regression methods. In contrast to the cost function approach, the IDF does not require input prices which are usually unavailable or measured imprecisely. In addition, we can account for equity and physical capital in the IDF. These variables are either excluded from the analysis (especially in a cost function approach) or treated as quasi-fixed inputs, because their prices are not readily available. In our application, we use data for bank holding companies and large commercial banks in the U.S. from 2000 to 2010. We find that although some of these institutions enjoy increasing returns to scale, scale economies are economically small. Thus, concerns about potential cost increases arising from breaking up large banking organizations seem exaggerated, especially from the scale economies point of view.
publishDate 2015
dc.date.available.none.fl_str_mv 2015-11-06T21:15:34Z
dc.date.issued.none.fl_str_mv 2015
dc.date.accessioned.none.fl_str_mv 2015-11-06T21:15:34Z
dc.date.none.fl_str_mv 2015
dc.type.eng.fl_str_mv article
info:eu-repo/semantics/article
info:eu-repo/semantics/publishedVersion
dc.type.coarversion.fl_str_mv http://purl.org/coar/version/c_970fb48d4fbd8a85
dc.type.coar.fl_str_mv http://purl.org/coar/resource_type/c_6501
http://purl.org/coar/resource_type/c_2df8fbb1
dc.type.local.spa.fl_str_mv Artículo
dc.type.hasVersion.spa.fl_str_mv Obra publicada
dc.type.hasVersion.eng.fl_str_mv publishedVersion
status_str publishedVersion
dc.identifier.issn.none.fl_str_mv 0377-7332
dc.identifier.uri.none.fl_str_mv http://hdl.handle.net/10784/7613
dc.identifier.doi.none.fl_str_mv 10.1007/s00181-014-0831-9
identifier_str_mv 0377-7332
10.1007/s00181-014-0831-9
url http://hdl.handle.net/10784/7613
dc.language.iso.eng.fl_str_mv eng
language eng
dc.relation.ispartof.spa.fl_str_mv Empirical Economics. Vol. 48, (1), 2015, pp.143-168
dc.relation.isversionof.none.fl_str_mv http://link.springer.com/article/10.1007/s00181-014-0831-9
dc.relation.uri.none.fl_str_mv http://link.springer.com/article/10.1007/s00181-014-0831-9
dc.rights.eng.fl_str_mv restrictedAccess
dc.rights.spa.fl_str_mv © Springer International Publishing AG, Part of Springer Science+Business Media
dc.rights.coar.fl_str_mv http://purl.org/coar/access_right/c_16ec
dc.rights.local.spa.fl_str_mv Acceso restringido
rights_invalid_str_mv restrictedAccess
© Springer International Publishing AG, Part of Springer Science+Business Media
Acceso restringido
http://purl.org/coar/access_right/c_16ec
dc.publisher.eng.fl_str_mv Springer International Publishing 
dc.source.spa.fl_str_mv Empirical Economics. Vol. 48, (1), 2015, pp.143-168
institution Universidad EAFIT
bitstream.url.fl_str_mv https://repository.eafit.edu.co/bitstreams/4781c051-09d1-48b4-a564-c051efcb5861/download
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repository.name.fl_str_mv Repositorio Institucional Universidad EAFIT
repository.mail.fl_str_mv repositorio@eafit.edu.co
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